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IEEE/CAA Journal of Automatica Sinica

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D.-Y. Zhou, X. Xue, Q. Ma, C. Guo, L.-Z. Cui, Y.-L. Tian, J. Yang, and F.-Y. Wang, “Federated experiments: Generative causal inference powered by LLM-based agents simulation and RAG-based domain docking,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 11, pp. 1–4, Nov. 2024. doi: 10.1109/JAS.2024.124671
Citation: D.-Y. Zhou, X. Xue, Q. Ma, C. Guo, L.-Z. Cui, Y.-L. Tian, J. Yang, and F.-Y. Wang, “Federated experiments: Generative causal inference powered by LLM-based agents simulation and RAG-based domain docking,” IEEE/CAA J. Autom. Sinica, vol. 11, no. 11, pp. 1–4, Nov. 2024. doi: 10.1109/JAS.2024.124671

Federated Experiments: Generative Causal Inference Powered by LLM-based Agents Simulation and RAG-based Domain Docking

doi: 10.1109/JAS.2024.124671
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  • [1]
    X. Xue, F. Chen, D. Zhou, et al., “Computational experiments for complex social systems—Part I: The customization of computational model,” IEEE Transactions on Computational Social Systems, vol. 9, no. 5, pp. 1330−1344, 2021.
    [2]
    S. Minaee, T. Mikolov, N. Nikzad, et al., “Large language models: A survey,” arXiv preprint arXiv: 2402.06196, 2024.
    [3]
    S. Siriwardhana, R. Weerasekera, E. Wen, et al., “Improving the domain adaptation of retrieval augmented generation (RAG) models for open domain question answering.” Transactions of the Association for Computational Linguistics, vol. 11, pp. 1–17, 2023. doi: 10.1162/tacl_a_00530
    [4]
    X. Dai, C. Guo, Y. Tang, et al., “VistaRAG: Toward safe and trustworthy autonomous driving through retrieval-augmented generation,” IEEE Trans. Intelligent Vehicles, vol. 9, no. 4, pp. 4579–4582, 2024. doi: 10.1109/TIV.2024.3396450
    [5]
    F.-Y. Wang, “Federated ecology: From federated data to federated intelligence.” Chinese Journal of Intelligent Science and Technology, vol. 2, no. 4, pp. 305–311, 2020.
    [6]
    R. Scotland, “What is parallelism?” Evolution & Development, vol. 12, no. 24, pp. 106854, 2011.
    [7]
    X. Xue, G. Li, D. Zhou, et al., “Research roadmap of service ecosystems: A crowd intelligence perspective,” International Journal of Crowd Science, vol. 6, no. 4, pp. 195–222, 2022.
    [8]
    F.-Y. Wang, “Computational experiments for behavior analysis and decision evaluation of complex systems,” Journal of System Simulation, vol. 16, no. 5, pp. 893–897, 2004.
    [9]
    S. De Marchi and S. E. Page, “Agent-based models,” Annual Review of Political Science, vol. 17, pp. 1–20, 2014. doi: 10.1146/annurev-polisci-080812-191558
    [10]
    M. A. Janssen and W. Jager, “Fashions, habits and changing preferences: Simulation of psychological factors affecting market dynamics,” Journal of Economic Psychology, vol. 22, no. 6, pp. 745–772, 2001. doi: 10.1016/S0167-4870(01)00063-0
    [11]
    B. Pietzsch, S. Fiedler, K. G. Mertens, et al., “Metamodels for evaluating, calibrating and applying agent-based models: A review,” The Journal of Academic Social Science Studies, vol. 23, no. 2, 2020.
    [12]
    T. Lux and R. C. J. Zwinkels, “Empirical validation of agent-based models,” Handbook of Computational Economics (Elsevier), vol. 4, pp. 437–488, 2018.
    [13]
    L. Wang, C. Ma, et al., “A survey on large language model based autonomous agents,” Frontiers of Computer Science, vol. 18, no. 6, pp. 1–26, 2024.
    [14]
    H. Wang, W. Huang, Y. Deng, et al., “UniMS-RAG: A unified multi-source retrieval-augmented generation for personalized dialogue systems”, arXiv preprint arXiv: 2401.13256. 2024.
    [15]
    K. Nedas, M. Egenhofer, “Spatial-scene similarity queries,” Transacti ons in GIS, vol. 12, no. 6, pp. 661–681, 2008. doi: 10.1111/j.1467-9671.2008.01127.x

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